Munich Center of the Learning Sciences
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Project Area B

Research goal

Identify conditions of effective personalization of learning with simulations when social interaction, collaboration, and feedback are of particular importance.

Selected publications

  • Bauer, E., Heitzmann, N., & Fischer, F. (2022). Simulation-based learning in higher education and professional training: Approximations of practice through representational scaffolding. Studies in Educational Evaluation, 75, Article 101213. https://doi.org/10.1016/j.stueduc.2022.101213
  • Bauer, E., Sailer, M., Kiesewetter, J., Fischer, M. R., & Fischer, F. (2022). Diagnostic argumentation in teacher education: Making the case for justification, disconfirmation, and transparency. Frontiers in Education, 7, Article 977631. https://doi.org/10.3389/feduc.2022.977631
  • Fischer, F., Bauer, E., Seidel, T., Schmidmaier, R., Radkowitsch, A., Neuhaus, B. J., Hofer, S. I., Sommerhoff, D., Ufer, S., Kuhn, J., Küchemann, S., Sailer, M., Koenen, J., Gartmeier, M., Berberat, P., Frenzel, A., Heitzmann, N., Holzberger, D., Pfeffer, J., Lewalter, D., Niklas, F., Schmidt-Hertha, B., Gollwitzer, M., Vorholzer, A., Chernikova, O., Schons, C., Pickal, A. J., Bannert, M., Michaeli, T., Stadler, M., & Fischer, M. R. (2022). Representational scaffolding in digital simulations – learning professional practices in higher education. Information and Learning Sciences, 123(11/12), 645-665. https://doi.org/10.1108/ILS-06-2022-0076
  • Fink, M. C., Heitzmann, N., Siebeck, M., Fischer, F., & Fischer, M. R. (2021). Learning to diagnose accurately through virtual patients: Do reflection phases have an added benefit? BMC medical education, 21, 523. https://doi.org/10.1186/s12909-021-02937-9 
  • Fink, M. C., Reitmeier, V., Stadler, M., Siebeck, M., Fischer, F., & Fischer, M. R. (2021). Assessment of diagnostic competences with standardized patients versus virtual patients: Experimental study in the context of history taking. Journal of Medical Internet Research. https://doi.org/10.2196/21196
  • Heitzmann, N., Opitz, A., Stadler, M., Sommerhoff, D., Fink, M. C., Obersteiner, A., Schmidmaier, R., Neuhaus, B. J., Ufer, S., Seidel, T., Fischer, M. R., & Fischer, F. (2021). Cross-Disciplinary Research on Learning and Instruction – Coming to Terms. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.562658
  • Radkowitsch, A., Sailer, M., Schmidmaier, R., Fischer, M.R., & Fischer, F. (2021). Learning to diagnose collaboratively – Effects of adaptive collaboration scripts in agent-based medical simulations. Learning and Instruction, 75. https://doi.org/10.1016/j.learninstruc.2021.101487
  • Chernikova, O., Heitzmann, N., Stadler, M., Holzberger, D., Seidel, T., & Fischer, F. (2020). Simulation-Based Learning in Higher Education: A Meta-Analysis. Review of Educational Research, 20(10), 1-43. https://doi.org/10.3102/0034654320933544
  • Fink, M.C., Radkowitsch, A., Bauer, E., Sailer, M., Kiesewetter, J., Schmidmaier, R., Siebeck, M., Fischer, F. & Fischer, M. (2020). Simulation research and design: a dual-level framework for multi-project research programs. Educational Technology Research and Development, 68(6). https://doi.org/10.1007/s11423-020-09876-0
  • Radkowitsch, A., Fischer, M. R., Schmidmaier, R., & Fischer, F. (2020). Learning to diagnose collaboratively: validating a simulation for medical students. GMS Journal for Medical Education, 37(5). doi: 10.3205/zma001344
  • Stadler, M., Radkowitsch, A., Schmidmaier, R., Fischer, M., & Fischer, F. (2020). Take your time: Invariance of time on-task in problem solving tasks across expertise levels. Psychological Test and Assessment Modeling, 62(4), 517-525. [online]
  • Heitzmann, N., Seidel, T., Opitz. A., Hetmanek, A., Wecker, C., Fischer, M., Ufer, S., Schmidmaier, R., Neuhaus, B., Siebeck, M., Stürmer, K., Obersteiner, A., Reiss, K., Girwidz, R., & Fischer, F. (2019). Facilitating Diagnostic Competences in Simulations: A Conceptual Framework and a Research Agenda for Medical and Teacher Education. Frontline Learning Research, 7(4), 1-24. https://doi.org/10.14786/flr.v7i4.384
  • Förtsch, C., Sommerhoff, D., Fischer, F., Fischer, M. R., Girwidz, R., Obersteiner, A., Reiss, K., Stürmer, K., Siebeck, M., Schmidmaier, R., Seidel, T., Ufer, S., Wecker, C., & Neuhaus, B. J. (2018). Systematizing Professional Knowledge of Medical Doctors and Teachers: Development of an Interdisciplinary Framework in the Context of Diagnostic Competences. Education Sciences, 8(4), 207. https://doi.org/10.3390/educsci8040207
  • Bauer, E., Sailer, M., Kiesewetter, J., Schulz, C., Gurevych, I. Fischer, M.R., & Fischer, F. (2022). Learning to Diagnose Students’ Behavioral, Developmental and Learning Disorders in a Simulation-Based Learning Environment for Pre-Service Teachers. In F. Fischer & A. Opitz (Eds.). Learning to Diagnose with Simulations - Examples from Teacher Education and Medical Education. Springer. https://doi.org/10.1007/978-3-030-89147-3_8 
  • Chernikova O., Heitzmann N., Opitz A., Seidel T., & Fischer F. (2022). A Theoretical Framework for Fostering Diagnostic Competences with Simulations in Higher Education. In: Fischer F., Opitz A. (Eds.). Learning to Diagnose with Simulations - Examples from Teacher Education and Medical Education. Springer. https://doi.org/10.1007/978-3-030-89147-3_2 
  • Fink M.C., Reitmeier V., Siebeck M., Fischer F., & Fischer M.R. (2022). Live and Video Simulations of Medical History-Taking: Theoretical Background, Design, Development, and Validation of a Learning Environment. In F. Fischer, & A. Opitz (Eds.). Learning to Diagnose with Simulations - Examples from Teacher Education and Medical Education. Springer. https://doi.org/10.1007/978-3-030-89147-3_9 
        • Opitz, A., Fischer, M. R., Seidel, T., & Fischer, F. (2022). Conclusions and Outlook: Toward more Systematic Research on the Use of Simulations in Higher Education. In F. Fischer, & A. Opitz (Eds.). Learning to Diagnose with Simulations - Examples from Teacher Education and Medical Education. Springer. https://link.springer.com/chapter/10.1007/978-3-030-89147-3_11 
          • Radkowitsch A., Sailer M., Fischer M.R., Schmidmaier R., & Fischer F. (2022). Diagnosing Collaboratively: A Theoretical Model and a Simulation-Based Learning Environment. In F. Fischer, & A. Opitz (Eds.). Learning to Diagnose with Simulations - Examples from Teacher Education and Medical Education. Springer. https://doi.org/10.1007/978-3-030-89147-3_10 
          • Richters, C., Stadler, M., Radkowitsch, A., Behrmann, F., Weidenbusch, M., Fischer, M.R., Schmidmaier, R., & Fischer, F. (2022). Making the rich even richer? Interaction of structured reflection with prior knowledge in collaborative medical simulations. In A. Weinberger, W. Chen, D. Hernández-Leo, & B.Che (Eds.), Proceedings of the 15th International Conference on Computer-Supported Collaborative Learning - CSCL 2022 (pp. 155-162). International Society of the Learning Sciences. https://2022.isls.org/proceedings/ --> Best Paper Award
          • Bauer, E., Greisel, M., Kuznetsov, I., Berndt, M., Kollar, I., Dresel, M., Fischer, M. R., & Fischer, F. (2023). Using natural language processing to support peer-feedback in the age of artificial intelligence: A cross-disciplinary framework and a research agenda. British Journal of Educational Technology, 54(5), 1222–1245. https://doi.org/10.1111/bjet.13336
          • Berndt, M., Strijbos, J.-W., & Fischer, F. (2018). Effects of written peer-feedback content and sender’s competence on perceptions, performance, and mindful cognitive processing. European Journal of Psychology of Education, 33(1), 31–49. https://doi.org/10.1007/s10212-017-0343-z
          • Brandl, L., Stadler, M., Richters, C., Radkowitsch, A., Fischer, M. R., Schmidmaier, R., & Fischer, F. (2024). Collaborative problem- solving in knowledge-rich domains: A multi-study structural equation model. International Journal of Computer-Supported Collaborative Learning, 19(3), 341-368. https://doi.org/10.1007/s11412-024-09425-4
          • Chernikova, O., Holzberger, D., Heitzmann, N., Stadler, M., Seidel, T., & Fischer, F. (2024). Where salience goes beyond authenticity. Zeitschrift für Pädagogische Psychologie, 38(1-2), 15–25. https://doi.org/10.1024/1010-0652/a000357
          • Kollar, I., & Fischer, F. (2010). Peer assessment as collaborative learning: A cognitive perspective. Learning and Instruction, 20(4), 344–348. https://doi.org/10.1016/j.learninstruc.2009.08.005
          • Machts, N., Chernikova, O., Jansen, T., Weidenbusch, M., Fischer, F., & Möller, J. (2024). Categorization of simulated diagnostic situations and the salience of diagnostic information. Zeitschrift Für Pädagogische Psychologie, 38(1-2), 3–13. https://doi.org/10.1024/1010-0652/a000364
          • Richters, C., Stadler, M., Radkowitsch, A., Schmidmaier, R., Fischer, M. R., & Fischer, F. (2023). Who is on the right track? Behavior-based prediction of diagnostic success in a collaborative diagnostic reasoning simulation. Large-Scale Assessments in Education, 11(1). https://doi.org/10.1186/s40536-023-00151-1
          • Richters, C., Schmidmaier, R., Popov, V., Schredelseker J., Fischer, F., & Fischer, M. R. (2024). Intervention skills – a neglected field of research in medical education and beyond. GMS Journal for Medical Education, 41(4), Article Doc48. https://doi.org/10.3205/zma001703
          • Bannert, M., Reimann, P., & Sonnenberg, C. (2014). Process mining techniques for analysing patterns and strategies in students' self-regulated learning. Metacognition and Learning, 9(2), 161-185. https://doi.org/10.1007/s11409-013-9107-6
          • Braun, L.T., Zottmann, J.M., Adolf, C., Lottspeich, C., Then, C., Wirth, S., Fischer, M.R. & Schmidmaier, R. (2017). Representation scaffolds improve diagnostic efficiency in medical students. Medical Education, 51(11), 1118-1126. https://doi.org/10.1111/medu.13355
          • Braun, L. T., Lenzer, B., Fischer, M. R., & Schmidmaier R. (2019). Complexity of clinical cases in simulated learning environments: proposal for a scoring system. GMS Journal for Medical Education, 36(6), Article Doc80. https://doi.org/10.3205/zma001288
          • Molenaar, I., de Mooij, S., Azevedo, R., Bannert, M., Järvelä, S., & Gasevic, D. (2023). Measuring self-regulated learning and the role of AI: Five years of research using multimodal multichannel data. Computers in Human Behavior, 139, 107540. https://doi.org/10.1016/j.chb.2022.107540
          • Richters, C., Stadler, M., Radkowitsch, A., Behrmann, F., Weidenbusch, M., Fischer, M.R., Schmidmaier, R., & Fischer, F. (2024a). Fostering collaboration in simulations: How advanced learners benefit from collaboration scripts and reflection. Learning and Instruction, 93, 101912. https://doi.org/10.1016/j.learninstruc.2024.101912
          • Tausendfreund, O., Braun, L.T., & Schmidmaier, R. (2022). Types of therapeutic errors in the management of osteoporosis made by physicians and medical students. BMC Medical Education, 22, 323. https://doi.org/10.1186/s12909-022-03384-w 
          • Vogel, F., Wecker, C., Kollar, I. & Fischer, F. (2017). Socio-cognitive scaffolding with computer-supported collaboration scripts:A meta-analysis. Educational Psychology Review, 29(3), 477–511. https://doi.org/10.1007/s10648-016-9361-7
          • Wölfel, T., Beltermann, E., Lottspeich, C., Vietz, E., Fischer, M.R., & Schmidmaier, R. (2016). Medical ward round competence in internal medicine - an interview study towards an interprofessional development of an Entrustable Professional Activity (EPA). BMC Medical Education, 16, 174. https://doi.org/10.1186/s12909-016-0697-y
          • Braun, L. T., Zwaan, L., Kiesewetter, J., Fischer, M. R., & Schmidmaier, R. (2017b) Diagnostic errors by medical students: results of a prospective qualitative study. BMC Medical Education, 17(1), 191. https://doi.org/10.1186/s12909-017-1044-7
          • Chernikova, O., Heitzmann, N., Fink, M., Timothy, V., Seidel, T., & Fischer, F. (2020a). Facilitating Diagnostic Competences in Higher Education—A Meta-analysis in Medical and Teacher Education. Educational Psychology Review, 32(1), 157–196. (joint fist authorship). https://doi.org/10.1007/s10648-019-09492-2
          • Heitzmann, N., Fischer, F., & Fischer, M. R. (2018). Worked examples with errors: When self-explanation prompts hinder learning of teachers’ diagnostic competences on problem-based learning. Instructional Science, 46(2), 245-271. https://doi.org/10.1007/s11251-017-9432-2
          • Heitzmann, N., Stadler, M., Richters, C., Radkowitsch, A., Schmidmaier, R., Weidenbusch, M., & Fischer, M. R. (2023). Learners’ adjustment strategies following impasses in simulations—Effects of prior knowledge. Learning and Instruction, 83, 101632. https://doi.org/10.1016/j.learninstruc.2022.101632
          • Kron, S., Sommerhoff, D., Achtner, M., Stürmer, K., Wecker, C., Siebeck, M., & Ufer, S. (2022). Cognitive and Motivational Person Characteristics as Predictors of Diagnostic Performance: Combined Effects on Pre-Service Teachers’ Diagnostic Task Selection and Accuracy. Journal Für Mathematik-Didaktik, 43(1), 135–172. https://doi.org/10.1007/s13138-022-00200-2
          • Kyaruzi, F., Strijbos, J.-W., & Ufer, S. (2020). Impact of a Short-Term Professional Development Teacher Training on Students’ Perceptions and Use of Errors in Mathematics Learning. Frontiers in Education, 5. https://www.frontiersin.org/article/10.3389/feduc.2020.559122
          • Bauer, E., Sailer, M., Niklas, F., Greiff, S., Sarbu-Rothsching, S., Zottmann, J. M., Kiesewetter, J., Stadler, M., Fischer, M. R., Seidel, T., Urhahne, D., Sailer, M., & Fischer, F. (in press). AI-Based Adaptive Feedback in Simulations for Teacher Education: An Experimental Replication in the Field. Journal of Computer Assisted Learning. https://dx.doi.org/10.1111/jcal.13123
          • Berner, V.-D., Segerer, R., Oesterlen, E., Seitz-Stein, K., & Niklas, F. (2022). “Good” or “well calculated”? Effects of feedback on performance and self-concept of 5- to 7-year-old children in math. Educational Psychology, 42(3), 296-315. https://doi.org/10.1080/01443410.2021.2001790
          • Codreanu, E., Sommerhoff, D., Huber, S., Ufer, S., Seidel, T. (2020). Between authenticity and cognitive demand: Finding a balance in designing a video-based simulation in the context of mathematics teacher education. Teaching and Teacher Education, 95, Article 103146. https://doi.org/10.1016/j.tate.2020.103146
          • Kron, S., Sommerhoff, D., Achtner, M., Stürmer, K., Wecker, C., Siebeck, M., & Ufer, S. (2022). Cognitive and motivational person characteristics as predictors of diagnostic performance: Combined effects on pre-service teachers’ diagnostic task selection and accuracy. Journal für Mathematik-Didaktik, 43, 135-172. https://doi.org/10.1007/s13138-022-00200-2
          • Niklas, F. & Schneider, W. (2014). Casting the die before the die is cast: The importance of the home numeracy environment for preschool children. European Journal of Psychology of Education, 29(3), 327-345. https://doi.org/10.1007/s10212-013-0201-6
          • Sailer, M., Bauer, E., Hofmann, R., Kiesewetter, J., Glas, J., Gurevych, I., & Fischer, F. (2023). Adaptive feedback from artificial neural networks facilitates pre-service teachers’ diagnostic reasoning in simulation-based learning. Learning and Instruction, Article 101620. https://doi.org/10.1016/j.learninstruc.2022.101620
          • Sailer, M., Ninaus, M., Huber, S. E., Bauer, E., & Greiff, S. (2024). The End is the Beginning is the End: The closed-loop learning analytics framework. Computers in Human Behavior, Article 108305. https://doi.org/10.1016/j.chb.2024.108305 
          • Schmiedeler, S., Khambatta, K., Hartmann, J. & Niklas, F. (2020). „Wenn den Zappelphilipp die Aufschieberitis packt“: Zusammenhänge zwischen Prokrastination und ADHS-Symptomen und mögliche Mediatoren. Zeitschrift für Pädagogische Psychologie, 34, 23-34. https://doi.org/10.1024/1010-0652/a000248
          • Vogel, F., Kollar, I., Fischer, F., Reiss, K. & Ufer, S. (2022). Adaptable scaffolding of mathematical argumentation skills: The role of self-regulation when scaffolded with CSCL scripts and heuristic worked examples. International Journal of Computer-Supported Collaborative Learning, 17, 39–64. https://doi.org/10.1007/s11412-022-09363-z
          • Brandl, L., Stadler, M., Richters, C., Radkowitsch, A., Fischer, M. R., Schmidmaier, R., & Fischer, F. (2024). Collaborative problem-solving in knowledge-rich domains: A multi-study structural equation model. International Journal of Computer-Supported Collaborative Learning, 19, 341-368. https://doi.org/10.1007/s11412-024-09425-4
          • Gollwitzer, M., Magraw-Mickelson, Z., Vollan, B., & Süssenbach, P. (2021). Victim sensitivity in groups: When is one a detriment to all? Journal of Theoretical Social Psychology, 5(1), 3-13. https://doi.org/10.1002/jts5.76
          • Holzberger, D., Brandl, L., Stadler, M., Obersteiner, A., Chernikova, O., Pickal, A. J., Nickl, M., Richters, C., Kron, S., Wecker, C., Heitzmann, N., Irmer, M., Corves, C., Radkowitsch, A., Neuhaus, B. J., Fischer, M. R., Ufer, S., Fischer, F., Sommerhoff, D., Seidel, T. (2024, in-principle accepted). The interplay between expectancy and value and its generalizability across simulation-based learning environments: An individual participant data meta-analysis. Registered Report in Journal of Educational Psychology, in-principle accepted.
          • Holzberger, D., & Prestele, E. (2021). Teacher self-efficacy and self-reported cognitive activation and classroom management: A multilevel perspective on the role of school characteristics. Learning and Instruction, 76, Article 101513. https://doi.org/10.1016/j.learninstruc.2021.101513
          • Holzberger, D., Maurer, C., Kunina-Habenicht, O., & Kunter, M. (2021). Ready to teach? A profile analysis on cognitive and motivational-affective teacher characteristics at the end of pre-service teacher education and long-term effects on teachers’ occupational well-being. Teaching and Teacher Education, 100. https://doi.org/10.1016/j.tate.2021.103285
          • Magraw-Mickelson, Z., Süssenbach, P., & Gollwitzer, M. (2022). The virus of distrust: How one victim-sensitive group member can affect the entire group’s outcomes. European Journal of Social Psychology, 52(3), 487-499. https://doi.org/10.1002/ejsp.2832
          • Soellner, N., Eiberle, M., Berberat, P., Schulz, C., Hinzmann, D., Rath, S., Haseneder, R., & Gartmeier, M. (2022). Just showing is not enough: First-person-view-videos as a feedback tool in resuscitation. Studies in Educational Evaluation, 72, 101100. https://doi.org/10.1016/j.stueduc.2021.101100
          • Bonnes, C., Leiser, C., Schmidt-Hertha, B., Rott, K.J., & Hochholdinger, S. (2020). The relationship between trainers’ mediadidactical competence and media-didactical self-efficacy, attitudes and use of digital media in training. International Journal for Training & Development 24(1), 74-88. https://doi.org/10.1111/ijtd.12171
          • Graichen, M., Mikelskis-Seifert, S., Hinderer, L., Scharenberg, K.,& Rollett, W.(2024). Unveiling Potential: Fostering Students’ Self Concepts in Science Education by Designing Inclusive Educational Settings. Education Sciences 14(6), 632. https://doi.org/10.3390/educsci14060632
          • Jünger, J., Pante, S.V., Ackel-Eisnach, K., Wagener, S., & Fischer, M.R. (2020). Do it together! Conception and long-term results of the trans-institutional Master of Medical Education (MME) program in Germany. GMS Journal for Medical Education 37(3), Doc33. https://doi.org/10.3205/zma001326
          • Kiesewetter, J., Sailer, M., Jung, V.M., Schönberger, R., Bauer, E., Zottmann, JM., Hege, I., Zimmermann, H., Fischer, F., & Fischer, M.R. (2020). Learning clinical reasoning: how virtual patient case format and prior knowledge interact. BMC Medical Education 20(1), 73. https://doi.org/10.1186/s12909-020-1987-y
          • Kühl, S.J., Schneider, A., Kestler, H.A., Toberer, M., Kühl, M., & Fischer M.R. (2019). Investigating the self-study phase of an inverted biochemistry classroom - collaborative dyadic learning makes the difference. BMC Medical Education 19(1), 64. https://doi.org/10.1186/s12909-019-1497-y. PMID: 30819178; PMCID: PMC6393989
          • Rohs, M., Schmidt-Hertha, B., Rott, K., & Bolten, R. (2019). Measurement of media pedagogical competences of adult educators. European Journal for Research on the Education and Learning of Adults, 10(3), 304-324. https://doi.org/10.3384/rela.2000-7426.ojs393
          • Rott, K.J., Lao, L., Petridou, E., & Schmidt-Hertha, B. (2022). Needs and requirements for an additional AI qualification during dual vocational training: Results from studies of apprentices and teachers. Computers and Education: Artificial Intelligence, 100102. https://doi.org/10.1016/j.caeai.2022.100102
          • Sailer, M., Schultz-Pernice, F., & Fischer, F. (2021a). Contextual facilitators for learning activities involving technology in higher education: The C♭-model. Computers in Human Behavior, 121, 106794. https://doi.org/10.1016/j.chb.2021.106794
          • Schmidt-Hertha, B. (2020). Vermittlung medienpädagogischer Kompetenz in der Fort- und Weiterbildung von Lehrkräften. Zeitschrift für Pädagogik, 66(2), 191-207. https://doi.org/10.3262/ZP2002191
          • Tafertshofer, L., Werner, E.-M. & Schmidt-Hertha, B. (2018). Grundlagen der Reputation von Studienstandorten: Bewertungsmaßstäbe für die Qualität von Hochschulstandorten und Studiengängen aus der Sicht von sozialwissenschaftlichen Professorinnen und Professoren. Beiträge zur Hochschulforschung, 2018 (2), 68-88.